System and apparatus for automated quantitative assessment, optimization and logging of the effects of a therapy

ABSTRACT

A method for assessment, optimization and logging of the effects of a therapy for a medical condition, including (a) receiving into a signal processor input signals indicative of the subject&#39;s brain activity; (b) characterizing the spatio-temporal behavior of the brain activity using the signals; (c) delivering a therapy to a target tissue of the subject; (d) characterizing the spatio-temporal effect of the therapy on the brain activity; (e) in response to the characterizing, optimizing at least one parameter of the therapy if the brain activity has not been satisfactorily modified and/or has been adversely modified by the therapy; (f) characterizing the spatio-temporal effect of the at least one optimized parameter; and (g) logging to memory the at least one optimized parameter. A computer readable program storage unit encoded with instructions that, when executed by a computer, performs the method.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to and is a continuation application ofU.S. patent application Ser. No. 15/586,433 filed on May 4, 2017,entitled “SYSTEM AND APPARATUS FOR AUTOMATED QUANTITATIVE ASSESSMENT,OPTIMIZATION AND LOGGING OF THE EFFECTS OF A THERAPY”, which claimspriority to and is a continuation application of U.S. patent applicationSer. No. 14,034,292 filed on Sep. 23, 2013 (now U.S. Pat. No.9,656,075), entitled “SYSTEM AND APPARATUS FOR AUTOMATED QUANTITATIVEASSESSMENT, OPTIMIZATION AND LOGGING OF THE EFFECTS OF A THERAPY”, whichclaims priority to and is a divisional application of U.S. patentapplication Ser. No. 12/729,093 filed on Mar. 22, 2010 (now U.S. Pat.No. 8,560,073), entitled “SYSTEM AND APPARATUS FOR AUTOMATEDQUANTITATIVE ASSESSMENT, OPTIMIZATION AND LOGGING OF THE EFFECTS OF ATHERAPY”, which claims priority to Provisional Application No.61/210,850, filed on Mar. 23, 2009 which are all incorporated in theirentireties by reference.

Safe and effective therapies for pharmaco-resistant seizures are a majorunmet medical need affecting approximately 36% of all epileptics (˜1.1million in the US and ˜18 million worldwide). These subjects have poorquality of life, the large majority are unemployed, suffer fromdepression and are 40 times more likely to die suddenly than age-matchedsubjects in the general population. Brain electrical stimulation, eitherdirectly or indirectly (vagus nerve stimulation), and contingent(triggered by the onset of seizures) or non-contingent (e.g., periodic,round-the-clock), and other therapies such as localized cooling of theepileptogenic zone or direct delivery of drugs to it, hold great promisefor these patients. However, in light of the results of large recentclinical trials showing a modest mean decrease in seizure frequency of40-60% on patients than remain on multiple anti-seizure drugs,optimization is required if they are meet efficaciously andcost-effectively this medical need. This invention addresses in a novel,effective, and systematic manner, the complex and demanding task ofoptimization of interventional brain therapies for control ofundesirable changes of state. In its preferred embodiment this inventionaddresses brain state changes and in particular epileptic seizures.Therapies for other neurological (e.g., pain, movement), psychiatric(e.g., mood; obsessive compulsive), and cardiac (e.g., arrhythmias)disorders may be optimized using the approaches described herein.

Epileptic seizures occur with or without discernible or visible clinicalmanifestations.

In the case of seizures originating from discrete brain regions (knownas partial or “focal” seizures) the electrical abnormalities usuallyprecede the first clinical manifestation (subjective or objective) andin a large number of these patients, impairment or loss ofresponsiveness occurs some time after the first clinical manifestation.Also, if the seizure becomes secondarily generalized, loss ofconsciousness (to be distinguished from loss of responsiveness) occursafter loss of responsiveness. Commonly, abnormal electrical activityoutlasts the loss of consciousness and consciousness is regained beforeresponsiveness returns to normal (for the patient) levels. In certainepileptic brains the transition from the non-seizure to the seizurestate may be gradual, providing a window for prediction and interventionbefore the transition is complete. Degree of responsiveness may betested and quantified in real-time using a wide variety of availabletests.

Therapy for control of disorders such as epilepsy which manifestintermittently, aperiodically and briefly (ranging from seconds torarely >2 min) and are classified as dynamic, meaning that state changes(from normal to abnormal and vice-versa) are caused by changes in thesystem's control parameter(s) are specially challenging. To increase theprobability of therapeutic success local, global, structural, dynamical,and state factors influencing the state change, must be identified andmeasured with useful precision and at informative time scales. Theseconcepts and considerations required to formulate treatment andoptimization strategies are lacking in the state-of-the art therapies.

While this invention is aimed at optimizing a therapy, nothing in itsspecification precludes delivery of a therapy prior to optimization orwithout optimization. Indeed, optimization cannot take place if atherapy has not been administered and its effects (beneficial anddetrimental) quantified. If a therapy cannot be optimized (in terms ofincreasing its beneficial effects), optimization may be effected bydecreasing the number or intensity and duration of its adverse events.Adverse effects include but are not limited to increase in seizurefrequency or severity, cognitive impairment in functions such as memory,language, mood (depression or mania), psychosis. These adverse effectsmay be quantified using cognitive, electrical, thermal, optical andother signals and logged to computer memory. In the case of signals thatlack easily detectable or recognizable electrical or other correlates,they may be characterized using a semi-quantitative approach such aspsychiatric scales, care-giver observations or patient diaries.

The term “therapy” may be interchangeably used with the term control forwhich a theory exists (Control Theory) in the field of engineering.Since therapy and control share the same aim, it is appropriate to adoptcertain concepts form this theory as well as from the fields of dynamicsto generate a rational approach and strategy for the management ofpharmaco-resistant seizures.

The epileptic brain may be conceptualized as a non-stationary,non-linear, “noisy” system that undergoes sudden unexplained reversibletransitions from the non-seizure state. The manner in which thistransition occurs may be “gradual” (through a process of “attractordeformation”) or sudden (through a “leap” from one state to another) asobserved in bi-stable or multi-stable systems. Dynamical theory teachesthat a system may be defined by its dimension (which corresponds to theminimum number of variables required to specify it). The identificationof a system's dimension greatly benefits from the identification of aspatio-temporal scale of observation that corresponds to arepresentative sample of the system (so-called mesoscopic scale), thusobviating the need to study the whole system at all scales, a dauntingand impracticable task in the case of the mammalian brain. The epilepticbrain's dimensionality and its mesoscopic scale have not beeneffectively specified to date. This knowledge void forces the treatmentof the brain as a “black-box”.

While by definition a “black-box” is not amenable to direct inquiry, itcan be indirectly studied through perturbations of system inputs. Aknown, well characterized input is “fed” into the “black-box” and theoutput is carefully recorded and characterized quantitatively orqualitatively and compared to the input. Transformations, if any to theinput properties provide indirect but useful information about the“black-box” that may be captured mathematically as transfer functions.For example, if doubling the amplitude of the input translates intodoubling of the output, the system is considered linear. However ifdoubling the input causes an exponential increase in the output, thesystem is non-linear (likely the brain's case). If sine waves are fedinto the black box and 60 Hz. activity appear on them as they exit thebox, it is reasonable to infer that the box corrupts the waves and is“noisy”. Successful control of the behavior of “black-boxes” cannotoccur if the measurements of its output are not representative of thestate(s) and site(s) from where they are obtained, reasonably preciseand also reproducible from measurement to measurement.

Global and local factors (many state-dependent) also shape the responseto therapies. For example, the rate and direction of diffusion ofparticles and molecules in animal tissue (e.g. brain), depends onmultiple factors including size, chemical valence and the size andtortuosity of the extracellular space. In certain tissues, such as thebrain's, the average values of the dielectric constant, or permittivity,and of the resistance are not equal at all points of the volume whichthe particles and molecules occupy. This anisotropy, which varies by afactor of 5-10 between two orthogonally-selected directions, such asbetween the vertical (or radial) and horizontal (or transverse)directions in a brain's cortex or its axons, ensures that diffusion ofendogenous and exogenous (e.g., electrical stimulation) currents is nothomogenous. This lack of homogeneity (and of isotropy) in the case of atherapy (e.g., electrical stimulation) that must diffuse through thetissue to exert its beneficial action is likely to decrease efficacy, afeature that must be considered for control and optimization purposes.

The diffusions of electrical currents within the brain, which as vectorshave both magnitude (potential) and direction, are the result ofelectrostatic forces caused by the transient accumulation of charges andalso of electrodynamic actions arising from ionic or electronic currentsin the volume which surrounds the local accumulations of such charges.Intracortical diffusion of electrical charges (ions) and currents, takesplace at several spatial domains or scales (active membrane sites,cells, columns and the cortical synergic groups where they flowdifferentially through the lattice of intercellular spaces and throughthe network of glial cells. These flows occur through a large number ofroutes at their disposal, each route being the path for only a smallpart of the total current (Kirchhoff's law), a “fractionation” that mayresult in insufficient (or excessive) current densities and low or noefficacy or adverse effects in certain sites.

An additional challenge to controlling brain state changes is thattissue anisotropy is not uniform or constant but it varies as a functionof differences in cortical cytoarchitecture and of the state ofactivation within the volume where putative (endogenous) or exogenous(e.g., electrical stimulation) currents diffuse. These inter-regional orareal differences translate into time- and space-constant differencesthat make the probability of generation of action potentials and theirconduction velocities behave differentially. When present, thesedifferences lead to the spatio-temporal dispersion of endogenous orexogenous (e.g., electrical stimulation) currents and to a lower thandesirable current flux through the region of interest—and thuspotentially to loss of therapeutic efficacy. However, the opposite mayalso occur and current flux may be higher than desirable for efficaciouscontrol or safety purposes. The fact that electrical currents bothtrigger and control seizures depending on the stimulation parametersused, such as frequency and intensity, among many other factors, shouldnot be ignored by those who use this modality for therapeutic purposes.In addition to the inherent widespread morphological or structuralanisotropy of nervous tissue, diffusion of electrical potentials alsodepend on: a) the state (at both global and local levels and at long andshort time scales) of the network; b) on the level (spike frequency) andpattern of spike activity and the “valence” (inhibitory or excitatory)of inputs and outputs or efferences, which are likely reflected inchanges in tissue conductivity/ diffusivity and responsivity to bothendogenous and exogenous currents. For example, tissue resistivity isaltered by bursts of epileptiform discharges of only a few secondsduration and frequent seizures often alter tissue osmolality, both ofwhich are likely to negatively impact therapeutic efficacy, unless thesefactors are taken into account and measured.

As for electrical stimulation, the most investigated therapeuticmodality for pharmaco-resistant epilepsies, the electric field E, atevery point i on the surface of a charged needle (which closelyapproximates in shape the electrodes used in humans for treatmentpurposes) is similar to the set of diffusion limited aggregation growthprobabilities and in this sense, the electric field E, is also amulti-fractal set. This means that different “regions” in the electricfield (and by extension in the tissue where the field is active) are notonly fractal but have different fractal values or properties atdifferent points. That an electric field as described above is amulti-fractal set brings to the fore one of the central themes of thiswork, the spatio-temporal “inhomogeneity” of a therapy (electrical) andthe requirement (for optimization of this treatment modality) to applyconcepts (from multi-fractal theory, among others) to quantitativelycharacterize this complex phenomenon.

Prior art therapies also ignore the dampening and the linear andnon-linear distortions of frequency, phase, harmonics and amplitude thatinvariably occur as currents travel through brain tissue. Morespecifically, prior art therapies and interventions for blocking,abating, or preventing undesirable state changes ignore tissueanisotropy, dielectric hysteresis, state and circadian influences atlocal and global scales and the changing nature (non-stationarity) inthe type, pattern and level of neuronal activity as a function of stateand time as reflected in intra-individual and inter-individualdifferences in seizures.

The present inventor has investigated the foregoing issues in conductingresearch to improve therapies available to epileptic patients. FIGS.1-33 depict the power spectrum (a representative estimation of brainactivity) of neuronal activity recorded over 162 hours from the samesite in the same human subjects. These figures demonstrate how theactivity of the epileptogenic zone as reflected in the power spectrumchanges as a function of time. A look at these spectrograms and at thetemporal evolution of the values of a) the decimal logarithm of thestandard deviation (FIG. 34(a)); b) of the generalized Hurst exponent(FIG. 34(b)) and of the singularity spectra width values (FIG. 34(c)) oftwo seizures recorded from 11 subjects (each subject's seizures are inthe same row), point clearly to the importance of tailoring therapy tointra- and inter-individual differences; it is improbable thatelectrical stimulation with fixed parameters (the current state-ofthe-art) delivered to each of these seizures will have the same effect,let alone that it will be uniformly beneficial.

The inhomogeneity/lacunarity of involvement of tissue during anundesirable event (see contour plots of FIG. 35; upper panel: seizureonset right temporal lobe shown at high temporal resolution; lower panelshows the spatio-temporal evolution of the seizure over both temporallobes at low temporal resolution) underscores the importance ofquantifying and accounting for lack of uniform tissue involvement(inhomogeneity) by these abnormal events.

If seizure properties features are determined using spectral methods andclassified into clusters (each cluster represents a given type ofseizure) using vectors of their properties (e.g., the log of thestandard deviation, the singularity spectra width values, etc.), thepresent worker have found that there is more than one cluster or seizuretype for each subject, for seizures originating from the same site, andthat the number of clusters changes in time, suggesting correspondingchanges in the number of main “modes” of neural activity.

Seizures may have a latent circadian periodicity which could beextracted as periodicity in the variation of the pseudo-F-statisticmaximum values. This periodicity may disappear as a function of time,state and other factors. FIG. 36 depicts the time evolution of thevalues of the Pseudo-F statistic (a measure of cluster tightness) ofseizures recorded from the same site and from the same individual.Notice the red clouds seen at 1.2 (˜12 hr) and 1.4 (˜24 hr) in they-axis (the y-axis is the log of time) and present from the start of therecording and indicative of a circadian tendency for seizure propertiesto cluster, that is, to be highly similar, vanishes after approximately110 hours (x-axis, time in hours) indicating the loss of the circadiantrend. This observation further exposes the variability of abnormalbrain activity over intermediate time scales (tens of hours),variability that must be detected and measured to optimize (as afunction of time) therapeutic efficacy.

Other important factors that are ignored by current therapies are: (i)seizure blockage does not necessarily translate into prevention of lossof cognitive functions, the most disabling seizure symptom; (ii) theinherent and inevitable delay (vide supra) in arrival of the therapy toits target site, delay which depends among others on the therapeuticmodality (relatively short for electrical currents and relatively longfor drugs and thermal energy); (iii) the degree (low or high) ofmorphological similarity or rhythmicity among waves that make up aseizure, determines the probability (high if the waves are highlysimilar) of blockage especially if electrical stimulation is the therapyof choice; (iv) the lack of uniformity in flow direction and in densityof both the abnormal activity and the therapy, as well the differencesin their speed of propagation, their synchronization levels and degreeof rhythmicity.

SUMMARY OF THE INVENTION

In one embodiment, the present invention provides a method forassessment, optimization and logging of the effects of a therapy for amedical condition. In one embodiment, the method comprises:

(a) receiving into a signal processor input signals indicative of thesubject's brain activity;

(b) characterizing the spatio-temporal behavior of the brain activityusing the signals;

(c) delivering a therapy to a target tissue of the subject;

(d) characterizing the spatio-temporal effect of the therapy on thebrain activity;

(e) in response to the characterizing, optimizing at least one parameterof the therapy if the brain activity has not been satisfactorilymodified and/or has been adversely modified by the therapy;

(f) characterizing the spatio-temporal effect of the at least oneoptimized parameter; and

(g) logging to memory the at least one optimized parameter.

The present invention also provides a method for optimizing the effectof a therapy. In one embodiment, the method comprises determining a waverhythmicity of brain activity of a subject, and applying a therapy to atarget tissue of the subject at a first time, wherein the target tissueand the first time are based upon the wave rhythmicity.

The present invention also provides a method for optimizing the effectof a therapy. In one embodiment, the method comprises estimating thelevel of synchrony within one brain epileptogenic region, anddetermining if the level of synchrony is above or below a valueassociated with a high probability of blockage of an epileptic eventwhen the therapy is applied. In a further embodiment, delivery of thetherapy is timed to coincide with the synchrony level reaching the valueassociated with the high probability of blockage of the epileptic event.

The present invention also provides a computer readable program storageunit encoded with instructions that, when executed by a computer,perform a method as described above and herein.

BRIEF DESCRIPTION OF THE DRAWING FIGURES

FIGS. 1-33 show three-dimensional power spectra of short ECoG segmentsfrom the same subject and from the same brain site, but at differenttimes of days, illustrating the changes in power at different bands as afunction of time, state, etc. This suggests non-stationarity of thesystem, a phenomenon that state of the art therapies fail address andwhich this invention addresses.

FIGS. 34(a), 34(b), and 34(c) show the evolution of the decimallogarithm (FIG. 34(a)), generalized Hurst exponents (FIG. 34(b)), andsingularity spectra (FIG. 34(c)) of seizures (two seizures/subject) ofEEG increments recorded from eleven subjects with pharmaco-resistantepilepsy. FIG. 34(a) shows an evolution of decimal logarithm of standarddeviation of EEG increments within adjacent time windows of the length 1second. Each individual has its own pattern of standard deviationevolution. Red vertical lines—clinical onset times, blue verticallines—expert visually scored seizures end times. Each row has twoseizures recorded from the same subject and from the same brain site.Notice intra- and inter-individual differences, that underscore theimportance of tracking as a function of time (e.g., time of day, week,month, etc.) and of state (e.g, awake versus asleep; if awake attentiveversus relaxed; if asleep in non-REM versus in REM sleep; if in non-REMin stage I versus III, etc.) their properties and using this informationto adapt and optimize therapy, both on a seizure-by seizure- and onindividual bases.

FIG. 35 shows contour plots of a single seizure. Notice spatial powerspectral differences over area of seizure origin (epileptogenic zone),which differences are indicative of inhomogeneity. Not shown are thedifferences in the temporal evolution of this abnormal activity at thedifferent sites, another type of inhomogeneity. Therapeutic efficacy maydepend on the ability to tailor time of delivery, intensity/dose, typeof therapy, location, geometric configuration and number of therapysources to the spatio-temporal characteristics and the evolution of theundesirable event.

FIG. 36 shows the decimal logarithm of the squared Morlet waveletcoefficient for the maximal Pseudostatistic F variation, in reference tothe clustering of seizures recorded from a subject (same brain site)over approximately 150 hours. A strong periodic component atapproximately 12 and 24 hours (see red cloud) is seen for the first 110hours, probably reflecting circadian influences. However, notice thatthis periodicity, weakens considerably after 110 hours, pointing againto the non-stationarity of undesirable events (seizures in this case)and the importance of tracking the evolution of their properties overmultiple temporal scales so as to optimize therapy.

FIG. 37(a) shows the effect of five cathodal monophasic (DC) pulses onsix different seizures, recorded from the same site. Notice thatseizures whose waves are highly similar or rhythmical (as quantified bythe rhythmicity index whose value (e.g., 0.91) appears to the left ofthe pulse artifacts and above the waves) are abated, while those whosewaves are somewhat dissimilar and have low rhythmicity are not.

FIG. 37(b) shows that even a single cathodal monophasic pulse mayabolish a highly rhythmical seizure, while having no effect on one withlow rhythmicity.

FIG. 37(c) shows an enlarged impulse or evoked response to monophasiccathodal stimulation of one of the seizures shown in FIG. 37(a). Theimpulse responses to cathodal stimulations show subtle phase shifts(phase resetting) which are predictive of a beneficial or non-beneficialresponse. Using available optimization search methods, the timing ofdelivery of a single (or very pulses) to cause the desirable(beneficial) phase may be found for each seizure.

FIGS. 38-39 show a flowchart depiction of one method, in accordance withthe present invention.

DETAILED DESCRIPTION OF THE INVENTION

The degree of morphological stereotypia (similarity) among waves(denoted herein as rhythmicity) that make up seizures is an indirectmeasure of neuronal synchronization within a region and between regions.The occurrence of trains of waves with highly similar waveforms(frequency and amplitude) within a brain region or between brain regionsmay be interpreted as an indication that these waves are generated byhighly similar and phase-locked generators. Rhythmicity is a novelmeasure of waveform stereotypia and indirectly of the spatio-temporalbehavior and synchronization of those waveforms' generators. Rhythmicitymay be measured using the autocorrelation function (ACF) of a (possiblypre-filtered) linearly detrended signal; normalization by total signalpower in the window is performed so that the ACF has a value of 1.0 atzero lag. The ACF may be written into a computer program for on-line(real-time) automated quantification and triggering of a therapy.

Neuronal rhythmicity for a time epoch of signal is defined as the valueof the ACF at the first local maximum to the right of the firstzero-uperossing. As the signal evolves, a sliding window technique isused to compute rhythmicity; values >0.6 indicate a high rhythmicity andhigh degree of dynamical coupling among the neurons generating thosewaves; values between 0.3 and 0.6 reflect moderate rhythmicity; andvalues <0.3 indicate low rhythmicity as seen in poorly organizedseizures. High rhythmicity (absolute or relative to their pre-ictalvalue) appears to be predictive of a beneficial response to brainelectrical stimulation (FIG. 37).

Since among several factors, the probability of seizure blockage usingelectrical currents seems dependent upon the degree of rhythmicity whichvaries during/within a seizure, the following strategy may prove usefulto increase the likelihood of blockage: the degree of neuronalsynchronization using a measure of rhythmicity or synchronization istracked and, if its value during a seizure is above or below a level orvalue associated with low probability of seizure blockage or attenuation(value which may vary between seizures from the same site, between brainregions and subjects) this measure's value is first decreased (if it isabove the value associated with high probability of a beneficialresponse) or increased (if below said value) by delivering appropriatelytimed monophasic, biphasic but not charge-balanced or charge-balancedpulses to a seizure, a step that is followed by re-delivery ofelectrical pulses timed to coincide with the decrease or increase inrhythmicity to within the values associated with high probability ofseizure blockage or attenuation. Thermal, drug, chemical, or opticalpulses may be delivered instead of or in addition to electrical ones.

Morphology/phase differences in response to electrical pulses arepredictive of a positive (seizure blockage) or negative (no blockage)therapeutic outcome and thus useful as feedback for optimizing atherapy. Several methods exist to compare the shape of waves (without orwith suitable transformations) including but not limited to root meansquare error and variations of the Dynamic Time Warping such as FastDynamic Time Warping, Adaptive Feature Based Dynamic Time Warping,Dynamic Derivative Time Warping, Qualitative Approximation to DynamicTime Warping. Other measures of distance (i.e., Euclidian, Manhattan,Chebyshev) may be used whenever applicable.

The probability of success in controlling undesirable events dependsamong other factors on: (a) the quality of spatio-temporal sampling ofthe signals which, in turn, is based on the type, geometry, and densityof electrode arrays and the stability and quality of theelectrode-tissue interface (U.S. Pat. No. 7,006,859, which is herebyincorporated herein by reference); (b) time and site of delivery of thetherapy in relation to the known or predicted onset of undesirablechanges; (c) parameter selection (frequency, intensity, waveform shape,etc.,) in the case of electrical stimulation, or drug type and dose inthe case of pharmacological therapy) as a function of space-timedynamics of the pathological process; (d) phase/time of the circadiancycle, when the undesirable changes occur, their intensity, duration andextent of spread; and (e) time elapsed from previous events and theirseverity (defined as the average of their intensity), duration andextent of spread. The prior art does not investigate, in eitherreal-time or off-line, and does not take into account these essentialconsiderations that are necessary to optimize control of the undesirableevents and prevent loss of function. Such considerations areparticularly important for preventing or blocking paroxysmal events suchas seizures, cardiac arrhythmias and pain whose behavior is shaped bythe substrate in which they occur along with other factors, some ofwhich are stochastic in nature.

Current methods or therapies for preventing, blocking or abatingundesirable or abnormal state changes that rely on vehicles or mediathat must diffuse or travel through tissue (from the source(s) to thetarget(s) to perform their actions) do not adequately account fordelays, uneven diffusion, and, in the case of oscillations/waves, thepossibility of formation of intermediate frequencies (heterodyning) oraliasing which, in turn, may result in undesirable (or desirable) butuncontrollable resonances with the frequency at which the neurons orheart cells oscillate.

Delays in diffusion resulting in uneven charge densities in the case ofcurrents, or of concentrations in the case of drugs/compounds, or oftemperatures in the case of cooling, in reaching their target likelycompromise efficacy and are not only the result of the degree of tissueanisotropy from where the state change takes place, but also of the sizeand macroscopic shape of the tissue. Size and macroscopic shape areimportant since the abnormal/undesirable activity also diffuses throughtissue with (a) certain speed(s) and direction(s). Improvements providedby our work include: (a) monitoring and controlling, in real time and atthe appropriate spatio-temporal scale, the space-time dynamics of adiffusive pathological process through optimization of the space-timedynamics of a diffusive therapy's (current densities, drug concentrationor temperature) direction, speed and extent of diffusion and (b) usingsignals and scales representative of the space-time dynamics of thepathological process as feedback to optimize in real-time (and off-linefor some applications) the space-time dynamics of the therapy.

This approach requires that the pathological events' signals or definingfeatures be adequately sampled spatio-temporally, and that timing ofdelivery, spatial diffusion and other features of the therapy beadjusted/controlled as a function of local and global space-timedynamics including those of the tissue and its components such asneurons, heart cells, etc. Since both the abnormal events and thetherapies are diffusive processes, spatio-temporal and geometric factorsthat cause differences in speed, direction, shape and distances betweenthe advancing fronts of, for example, a seizure and those of thetherapy, if not detected (or if detected but not timely corrected toavoid either undesirable resonances in the case of currents orinadequate charge density, drug concentrations or temperatures), arelikely to lack efficacy or exert a paradoxical effect, enhancing theundesirable event.

Linear and non-linear, parametric and non-parametric,geometric/graphical, statistical and conventional and high orderspectral methods exist for measuring, comparing and modeling brainactivity that may be used in this invention. Also, brain activity may berecorded in multiple domains: electrical, magnetic, thermal, optical,chemical, acoustic, mechanical (e.g. pressure or movement) in anycombination using commercially available sensors and analyzed usingmyriad available methods in the time or frequency domains. Models of: a)the abnormal activity (without treatment); b) the behavior of thetherapy in a controllable virtual medium and c) of the interactions ofthe abnormal activity and the therapy will be built for optimizationpurposes.

The present invention is the first to take into account that therapydelivered to tissue is influenced by the space-time-state tissuedynamics and, in this sense, is a dependent (not an independent)variable to which tools and means for addressing the inherent butmanageable limitations may be applied to adapt and optimize the therapyas needed not only for each subject, but also for the region from wherethe undesirable brain activity originates, the state of the system (e.g.awake vs. asleep) or time of day. The cytoarchitectonic diversity of thecortical mantle and of subcortical structures must be factored into thestrategies for therapy delivery. Location, type, size and number ofsensors for signal analyses and of therapy sources and type(s), are ofparamount importance for prevention, blockage or abatement of seizures,cardiac arrhythmias or pain. The inventive system disclosed herein hasthe ability to track/measure tissue resistivity, osmolality and tissueresponses, among other variables, and use latencies, amplitudes,waveforms/types and actual frequencies and periods of the responses tocreate maps as a function of time and state that are used to adjustautomatically or manually, therapies to improve safety, efficacy, andtolerability. Measurements of resistivity, osmolality, diffusivity,temperature, ionic and neurotransmitter concentrations, pressure/strain,motility, acoustic activity and of responses to electrical, chemical,physiological (e.g., visual), cognitive and affective stimulation may beperformed with commercially available sensors. Specific mention is madeof measuring cognitive functions, the most meaningful index oftherapeutic efficacy (especially in the case of partial complex orgeneralized seizures) and of using these measures to adapt and optimizetherapies.

The present invention overcomes the limitations of the prior art by: (a)quantifying and characterizing in real-time and, when advantageousoff-line, the electrical, chemical, thermal, mechanical, acoustic andcognitive (for brain) behavior of biological tissues at one or morespatial scales using passive and active probes; (b) recording withprecision and high fidelity not only the conventional frequencies(0.1-100 Hz) but also ultra-slow (e.g., 0.001 Hz) and ultra-fast (>500Hz) oscillations; (c) using this information to determine (and adapt andupdate as needed) the type of therapy, timing of delivery, location,geometry and number of therapy sources, duration and frequency/rate oftherapy delivery, the top priority being to prevent the event fromoccurring, the second one to block the event before the subject isimpaired, and the third one to lessen severity if blockage is notfeasible, so as to minimize dysfunction, delivering a warning ifprevention fails and logging to memory all relevant data about thespatio-temporal behavior of the brain activity and of the therapy.

Sensors of the present invention may be multimodal (e.g., electrical,optical, chemical, pressure, thermal, acoustic, etc.). Their numberlocation, functions, and status (active or dormant) may vary accordingto the task at hand. Similarly, therapy sources of the present inventionmay be multimodal (e.g., electrical, magnetic, chemical, thermal,mechanical, etc). Their number locations and functions, and status(active or dormant) may vary according to the task at hand.

In one embodiment, assessment of the spatio-temporal effects of therapyare performed in one or more dimensions, at one or more sites and at oneor more points in time and time-scales according to the following stepslisted in their order of execution: 1. Determine the spatio-temporalbehavior of a seizure and of a therapy response on-line or off-line,using the tissue electrical oscillations to estimate: a) power at one ormore frequencies; b) waveform or rhythmicity values of saidoscillations; c) rate of spread or diffusion the abnormal andtherapeutic electrical activity; d) extent of spread and the geometry orshape of the advancing abnormal and therapeutic electrical oscillationsgraphed, for example, as contour plots (see FIG. 35); e) changes inpower at one or more frequencies; f) rate of change in power; g) changesin rhythmicity values at one or more frequencies at one more sites, atone or more times; h) rate of change in rhythmicity values at one ormore frequencies; 2. Build probability density (or probabilitydistribution) functions using one or more values or their suitablemathematical transformation of each of the seizure signal and of thetherapy response features listed immediately above and create a libraryof catalogued events (seizures in this embodiment) and of treatmentmodalities and parameters; 3. Estimate in which interval (if at all) ofthe probability density function the values of the observed event and oftherapy response fall; 4. Based on where in the probability densityfunction the seizure or the response therapy) values fall, estimate theprobability with which: a) the seizure matches a known seizure type froma certain site in a certain subject and b) the therapy response isbeneficial or detrimental (for simplicity, modalities or treatmentparameters without any effect on seizures are classified asdetrimental); 5. If the seizure does not match with good probability aknown type, said seizure is saved into a library of unmatched events; ifthe therapy response is beneficial or detrimental, the modality andparameters used are saved to their respective libraries; 6. If thetherapy response is adverse, a modality or parameter optimization searchis launched and the results of each attempts are logged and saved toeither the beneficial or detrimental library and used to narrow thesearch space (FIGS. 38, 39). Existing search and optimization theory andmethods will be applied on-line or off-line in an automated anditerative manner using the feature values of the seizure and of thetherapy response as cost functions.

In other embodiments, other signals including but not limited tomagnetic, thermal, chemical or optical and their suitable features (e.g.concentrations of an ion in the case of chemical signals) or theirmathematical transformations may be used to build the statisticaldistributions and libraries of seizure features or properties (in one ormore dimensions, at one or more sites and at one or more times and timescales. The methods and processes described for electrical therapiesapply to thermal, pharmacologic and other therapy modalities.

The values of seizure properties or features and their spatio-temporalbehavior obtained without treatment are considered control valuesagainst which those obtained with treatment will be compared. Thesevalues may be ranked according to their magnitude and stratifiedaccording to site of origin, type and time of day, wake-sleep cycle, andcognitive state (relaxed awake or attentive awake) among others forlogging (with appropriate time stamping) and saving in the eventlibrary. The same procedure will be applied to the values of featuresobtained during the seizure-therapy interactions and the ensuingresponse.

Maps and other graphical means for plotting and displaying thespatiotemporal behavior of feature values of the seizures and of thetherapy response may be also used and logged and saved into librariesfor comparison purposes. Said comparison may be performed using shapesimilarity measures such as shape context, Hausdorff contour, Distanceset correspondence, Dice and cosine coefficients (in the case ofnumerical feature vectors) among many other available methods. Shapedescriptors such as D2 shape distributions, extended Gaussian maps,Gaussian Euclidian distance transforms may be also used for thispurpose. Shape matching, for comparing the shapes of seizure maps or oftherapy response maps, may be performed using the wavelet transformmodulus maxima, among other techniques known to the person of ordinaryskill in the art.

For electrical therapy (such as that described in U.S. Pat. No.6,934,580, hereby incorporated herein by reference), the followingapproaches may be pursued:

(a) generate direct and alternating currents, either simultaneously orsequentially in a predetermined pattern;

(b) deliver currents to multiple sites at the same or differentintensities possibly including a different intensity for the cathode asopposed to the corresponding anode wherein all anodes may have identicalor differing intensities wherein alternating currents can be deliveredwithout being fully charge-balanced, even though each phase for a givenintensity is balanced;

(c) deliver the currents to multiple sites at the same or differentfrequencies;

(d) deliver the currents to multiple sites using the same or differentpulse widths;

(e) deliver the currents to multiple sites using the same or differentwaveforms;

(f) deliver the currents to multiple sites using the same, different, orvarying polarities;

(g) deliver alternating currents to multiple sites using the same, fullyor incompletely charge-balanced pulses;

(h) change the number and/or geometric configuration or arrangements ofthe contacts to which current is delivered;

(i) deliver amplitude modulated currents to multiple sites usingsuitable carriers to thereby increase signal/noise ratios and enhancetissue penetration;

(j) deliver frequency modulated currents to multiple sites usingsuitable carriers to thereby increase signal/noise ratios and enhancetissue penetration;

(k) multiplex delivery of currents from their sources to take intoaccount (i) differences in speed of diffusion (particularly of itsfront) of the pathological process, and also (ii) distances between thesite of origin of pathologic process and therapy sources;

(l) change the orientation/direction, field size and strength of thetherapy;

(m) deliver fractal electrical waves;

(n) use multiple electrodes or therapy sources at single or multiplesites.

The concept of simultaneously delivering current at differentintensities, is equally applicable to frequencies, pulse widths andwaveforms. As an example of another application, electrodes may bearranged in a circle with a plurality of anodes encircling a single,centrally located cathode. For direct current applications, thepolarities may be changed for each pair of electrodes.

Other strategies by which therapies may be optimized include but are notlimited to:

1. Modification (augmentation or reduction) of their rate, direction,concentration, density of flow or diffusivity, and type of drug(s) orelectrical pulse(s) used.

2. Simultaneous or consecutive use of more than one therapeutic modality(e.g, electrical and thermal therapies, electrical and pharmacologicaltherapies, etc.).

Means by which diffusivity, direction, concentration, or density of atherapeutic medium may be modified include, but are not limited to:

1. Increasing or decreasing (a) tissue pressure using physical orchemical agents (e.g., manitol infusion to a certain region); (b)increasing or decreasing tissue temperature to create “sinks” or“barriers” to diffusion or to facilitate diffusion.

2. Changing the degree of lypophilicity or hydrophilicity of compoundsor changing surface tension of the extracellular space, or increasing ordecreasing the tortuosity (using mechanical or chemical means) of theextracellular space through which diffusion of ions, neurotransmitters,and other compounds takes place.

3. Releasing inactive compounds well in advance of events so as to allowthem to reach the target in sufficient concentration and activate themin response to the prediction or detection of an event such as aseizure. This may be accomplished for instance, via viral transfectionand implantation of fiberoptic fibers in the target area.

4. Increase the number of therapy source without causing undesirabletissue disruption through the use of micro- or nanodevices, or changingtheir location or orientation.

Some applications of the present invention may include logging to memorythe outcomes of therapy as a function of local space-time-statedynamics, and applying, on-line or off-line, existing search andoptimization methods in an automated and iterative manner, and usingcost functions, such as event severity or type of adverse event cause bythe therapy.

Spatio-temporal characterization of nervous activity (electrical,magnetic, thermal, chemical, acoustic, kinetic, pressure/load/strain,cognitive) may be performed using existing state-of-the-art linear ornon-linear, parametric or non-parametric uni- or multi-dimensionalsignal processing and analyses methods (See also U.S. Pat. Nos.5,995,868; 6,549,804; 6,768,969; 6,793,670; 6,934,580; 6,904,390;7,054,792; 7,188,053). Therapeutic modality and parameter search foroptimization of efficacy may be performed using methods such assimulated annealing, search, and genetic algorithms.

FIGS. 38-39 provide details about the process of therapy optimization,applicable to any therapeutic modality (pharmacological, thermal,electrical, ablative) and to any medical disorder.

All the approaches, methods and strategies described above may be usedto optimize the therapy by decreasing the frequency, intensity, durationof adverse events or by minimizing the probability of occurrence of themost serious, disabling or intolerable adverse effects, withoutnecessarily increasing the efficacy of the therapy.

In one embodiment, the present invention provides a method forassessment, optimization and logging of the effects of a therapy for amedical condition. In one embodiment, the method comprises:

(a) receiving into a signal processor input signals indicative of thesubject's brain activity;

(b) characterizing the spatio-temporal behavior of the brain activityusing the signals;

(c) delivering a therapy to a target tissue of the subject;

(d) characterizing the spatio-temporal effect of the therapy on thebrain activity;

(e) in response to the characterizing, optimizing at least one parameterof the therapy if the brain activity has not been satisfactorilymodified or has been adversely modified by the therapy;

(f) characterizing the spatio-temporal effect of the at least oneoptimized parameter; and

(g) logging to memory the at least one optimized parameter.

In one embodiment, the method further comprises logging to memory atleast one effect of the optimized therapy on the subject's brainactivity.

In one embodiment, step (d) comprises quantitatively characterizing thespatio-temporal effect of the therapy on the brain activity.Alternatively or in addition, in one embodiment, step (d) comprisessemi-quantitatively or qualitatively characterizing the spatio-temporaleffect of the therapy on the brain activity.

A variety of medical conditions may be considered. In one embodiment,the medical condition is epilepsy.

Various steps of the method can be performed at various times. In oneembodiment, steps (a) through (e) are performed at or before one or moreof the electrographic onset of a seizure, the clinical onset of aseizure, a loss of responsiveness, a loss of consciousness, theelectrographic termination of a seizure, a recovery of consciousness, ora recovery of responsiveness.

Any appropriate input signals may be used. In one embodiment, the inputsignals are one or more of electrical signals, magnetic signals, thermalsignals, optical signals, chemical signals, or cognitive signals.

In a further embodiment, when the input signals are electrical signals,characterizing the spatio-temporal behavior is performed in real-timeusing time-frequency-energy information in one, or more dimensions, atone or more time scales;

when the input signals are magnetic signals, characterizing thespatio-temporal behavior is performed in real-time usingtime-frequency-energy information in one or more dimensions and at oneor more time scales;

when the input signals are thermal signals, characterizing thespatio-temporal behavior is performed in real-time usingtime-frequency-energy information in one or more dimensions and at oneor more time scales;

when the input signals are optical signals, characterizing thespatio-temporal behavior is performed in real-time usingtime-frequency-energy information in one or more dimensions and at oneor more time-scales;

when the input signals are chemical signals, characterizing thespatio-temporal behavior is performed in real-time by measuring theirconcentrations and rate of diffusion through the extracellular space,rate of re-uptake into synapses or glia in one or more dimensions and atone or more time scales; or

when the input signals are cognitive signals, the input signals relateto at least one of reaction time, attention, verbal, non-verbal orprocedural short-term memory, verbal, non-verbal or procedural long-termmemory, language fluency or comprehension, visuo-spatial functions,auditory discrimination, visual discrimination, abstract reasoning,calculation, and judgment.

Any appropriate therapy for the medical condition may be considered. Inone embodiment, which may be appropriate when the medical condition isepilepsy, the therapy comprises one or more of an electrical therapy, amagnetic therapy, a chemical therapy, a heating therapy, a coolingtherapy, applying a pressure to a target tissue, applying a vacuum to atarget tissue, an optical therapy, a cognitive therapy, a sensorytherapy, or a motor therapy.

The therapy may be administered at any appropriate time, depending onthe medical condition, the therapy, and other factors apparent to theperson of ordinary skill in the art having the benefit of the presentdisclosure. In one embodiment, delivery of the therapy is based ondegradation of one or more cognitive signals. In a further embodiment,the cognitive signal is a level of responsiveness.

In one embodiment, optimizing comprises at least one of changing thetarget tissue, adding at least one therapy element, and changing adifferent type of therapy element.

The present invention also provides a method for optimizing the effectof a therapy. In one embodiment, the method comprises determining a waverhythmicity of brain activity of a subject, and applying a therapy to atarget tissue of the subject at a first time, wherein the target tissueand the first time are based upon the wave rhythmicity.

The present invention also provides a method for optimizing the effectof a therapy. In one embodiment, the method comprises estimating thelevel of synchrony within one brain epileptogenic region, anddetermining if the level of synchrony is above or below a valueassociated with a high probability of blockage of an epileptic eventwhen the therapy is applied. In a further embodiment, delivery of thetherapy is timed to coincide with the synchrony level reaching the valueassociated with the high probability of blockage of the epileptic event.

In one embodiment, the present invention provides a method of optimizingthe effects of a therapy. In one embodiment, the method comprises:

(a) determining the spatio-temporal behavior of one or more of apatient's seizures and the patient's response to a therapy in one ormore dimensions, at one or more sites, at one or more points in time, atone or more time-scales, and at one or more frequencies;

(b) building a probability density function based on the spatio-temporalbehavior;

(c) creating a library of seizure features;

(d) cataloging the one or more seizures according to a degree ofsimilarity to at least one of the seizure or therapy response features;

(e) classifying the one or more seizures as known or unknown ;

(f) creating a library of treatment and parameter modalities;

(g) classifying the treatment modalities as beneficial or detrimental;

(h) saving at least one feature of the one or more seizures into alibrary of unmatched events if it does not match a known seizure type;

(i) saving at least one therapy response to a beneficial treatmentlibrary if it is beneficial or to a detrimental treatment library if itis detrimental;

(j) optimizing the therapy parameters; and

(k) saving the optimized parameters.

Any one or more of the above steps may be performed on-line or off-line.

In one embodiment, determining the spatio-temporal behavior comprises atleast one of estimation of power and its rate of change, estimation ofone or more rhythmicity values and their rate of change, or estimationof the extent, rate of spread and shape of spread of abnormal andtherapeutic electrical activities.

In one embodiment, classifying the one or more seizures comprisesestimating an interval of the probability density function into whichthe values of the one or more seizures fall and classify the seizure asknown or unknown based on the interval.

In one embodiment, classifying the treatment modalities comprisesestimating the interval of the probability density function in which oneor more of the seizure or the response therapy fall, and using theestimate to determine the probability with which the seizure matches aknown seizure type from the site in the patient and the probability thatthe therapy response is beneficial or detrimental.

In one embodiment, the present invention provides a method forquantitative assessment, optimization and logging of the effects of atherapy for a medical condition. The method comprises:

(a) receiving into a signal processor input signals indicative of thesubject's brain activity and characterizing the spatio-temporal behaviorof the brain activity using the signals

(c) delivering a therapy to a target tissue of the subject;

(d) characterizing the spatio-temporal effect of the therapy on thesubject's brain activity;

(e) in response to the characterizing, optimizing the therapy if thesubject's brain activity has not been satisfactorily modified by thetherapy;

(f) characterizing the spatio-temporal effects of the parameters; and

(g) logging to memory the optimized therapy parameters .

In one embodiment, the method further comprises logging to memory atleast one effect of the optimized therapy on the subject's brainactivity.

In one embodiment, the method further comprises performing steps (a)through (f) at or before the onset of a brain activity of interest.

In one embodiment, steps (a) through (e) are performed before atransition into a seizure state is complete.

In another embodiment, steps (a) through (e) are performed at or afterthe electrographic onset of a seizure but before the first clinicalmanifestation (i.e. before clinical onset).

In another embodiment, steps (a) through (e) are performed at or afterclinical onset but before a loss of responsiveness.

In another embodiment, steps (a) through (e) are performed at or after aloss of responsiveness but before a loss of consciousness.

In another embodiment, steps (a) through (e) are performed at or after aloss of consciousness but before the termination of electrographicactivity.

In another embodiment, steps (a) through (e) are performed at or afterthe termination of electrographic activity but before a recovery ofconsciousness or before a recovery of responsiveness.

In another embodiment, steps (a) through (e) are performed at or after arecovery of responsiveness.

One or more of the various steps can be performed in real-time (i.e.,substantially without delay) or not in real-time. Alternatively or inaddition, one or more of the various steps can be performed by a firstdevice in proximity to or implanted into the body of the subject, or bya second device capable of being in communication with a first device.The second device may be continually in communication with the firstdevice, or may sporadically be in communication with the first device,such as only when uploading data from or downloading data to the firstdevice. Performance of one or more of steps (a) through (e) by a seconddevice in the latter scenario may be referred to as “off-line”performance. In one embodiment, steps (a) through (e) are performedoff-line.

The subject may have any medical condition of interest and/or any otherphysiological activity of interest. In one embodiment, the subject'sbrain activity of interest is an epileptic seizure.

In one embodiment, the input signals are electrical signals and thespatio-temporal behavior is characterized in real-time usingtime-frequency-energy information in one, or more dimensions, at one ormore time scales.

In a further embodiment, characterizing the spatio-temporal behavior ofthe brain activity comprises quantifying at least one of power atdifferent frequencies, the extent and shape of the spatial extent of theelectrical signals, and the direction and rate of spread of theelectrical signals.

In one embodiment, the input signals are magnetic signals and thespatio-temporal behavior is characterized in real-time usingtime-frequency-energy information in one or more dimensions and at oneor more time scales.

In a further embodiment, characterizing the spatio-temporal behavior ofthe brain activity comprises quantifying at least one of power atdifferent frequencies, the extent and shape of the spatial extent of themagnetic signals, and the direction and rate of spread of the magneticsignals.

In one embodiment, the input signals are thermal signals and thespatio-temporal behavior is characterized in real-time usingtime-frequency-energy information in one or more dimensions and at oneor more time scales. Though not to be bound by theory, doing so mayallow the operator of the method to quantify their space-time dynamics.

In one embodiment, the input signals are optical signals and thespatio-temporal behavior is characterized in real-time usingtime-frequency-energy information in one or more dimensions and at oneor more time-scales. Though not to be bound by theory, doing so mayallow the operator of the method to quantify their space-time dynamics.

In one embodiment, the input signals are chemical signals and thespatio-temporal behavior is characterized in real-time by measuringtheir concentrations and rate of diffusion through the extracellularspace, rate of re-uptake into synapses or glia in one or more dimensionsand at one or more time scales. Though not to be bound by theory, doingso may allow the operator of the method to quantify their space-timedynamics.

In one embodiment, the spatio-temporal effects characterized include atleast one of the power at different frequencies, wave morphology, rate,direction, density, spatial extent and shape of diffusion of the therapyin the tissue.

In a further embodiment, characterizing the spatio-temporal behavior ofthe brain activity comprises mapping the brain activity in one or moredimensions at one or more time scales, and characterizing thespatio-temporal effect of the therapy comprises mapping the effects inone or more dimensions and at one or more temporal scales, the methodfurther comprising comparing the brain activity map and thespatio-temporal therapy effects map.

In one embodiment, optimizing the therapy comprises optimizing at leastone of the site, rate of delivery, direction, density, and spatialextent of the therapy based upon the comparing the brain activity mapand the spatio-temporal therapy effects maps.

In a further embodiment, a brain activity of interest is an epilepticseizure, and wherein mapping the brain activity and mapping the therapyeffects are performed at a time when a seizure is not occurring.

In another further embodiment, mapping the brain activity and mappingthe effects are performed as a function of at least one of sleep-wakestate, circadian rhythms, and spatio-temporal dynamics history.

In one embodiment, optimizing comprises at least one of changing atarget tissue, adding at least one therapy element, and adding adifferent type of therapy element.

In one embodiment, optimizing comprises at least one of changing thetarget tissue, adding at least one therapy element, and changing adifferent type of therapy element.

In one embodiment, characterizing the spatio-temporal behavior of thebrain activity comprises performing at least one laminar field analysis.

In one embodiment fractal or multi-fractal analysis is performed tocharacterize the space-time dynamics of the abnormal activity and of thespatio-temporal therapy effects.

The signals can be collected, recorded, and stored using any appropriatetechnique, as a matter of routine experimentation to the person ofordinary skill in the art having the benefit of the present disclosure.In one embodiment, the signals are recorded between 0 (DC) and 10 KHz.In another embodiment, the signals are sampled at more than onefrequency and with more than one degree of precision.

Any therapy can be delivered to any target tissue of the subject. In oneembodiment, the delivered therapy comprises one or more of an electricaltherapy, a magnetic therapy, a chemical therapy, a heating therapy, acooling therapy, applying a pressure to a target tissue, applying avacuum to a target tissue, an optical therapy, a cognitive therapy, asensory therapy, and a motor therapy.

In one embodiment, therapy delivery is based on a degradation ofcognitive signals. In a further embodiment, the cognitive signal is alevel of responsiveness, such as may be determined from a complex timereaction test.

In one embodiment, therapy optimization is based on a measurement ofcognitive signals. In a further embodiment, the cognitive signal uponwhich therapy optimization is based is a level of responsiveness.

In one embodiment, the present invention also provides a method foroptimizing the effect of a medical therapy. In one embodiment, themethod comprises determining wave rhythmicity and applying a therapy toa target tissue at a first time, wherein the target tissue and the firsttime are based upon the wave rhythmicity.

In one embodiment, the present invention also provides a method foroptimizing the effect of a therapy. In one embodiment, the methodcomprises estimating the level of synchrony within one brainepileptogenic region, and determining if it is above or below a valueassociated with high probability of blockage when a therapy is applied.In a further embodiment, delivery of electrical, thermal or drug pulsesis timed to coincide with the synchrony level reaching a valueassociated with high probability of therapeutic efficacy.

In one embodiment, the present invention also provides a method forquantitative assessment, optimization, and logging of the adverseeffects of a therapy for a medical condition. In one embodiment, themethod comprises:

(a) receiving into a signal processor input signals indicative of thesubject's brain activity and characterizing the spatio-temporal behaviorof the brain activity using the signals;

(b) characterizing the spatio-temporal effect of the therapy on thesubject's brain activity;

(c) determining if the therapy causes adverse events;

(d) characterizing quantitatively, semi-quantitatively or qualitativelythe type, frequency, intensity and duration of the adverse effect;

(e) modifying the therapy to decrease the frequency, intensity,duration, or type of adverse effect; and

(f) logging to memory the optimized effects of the therapy on thesubject's brain activity.

In one embodiment, the present invention also provides a method forquantitative assessment, optimization and logging of the adverse effectsof a therapy for a medical condition. In one embodiment, the methodcomprises:

(a) receiving into a signal processor input signals indicative of thesubject's brain activity and characterizing the spatio-temporal behaviorof the brain activity using the signals;

(b) characterizing the spatio-temporal effect of the therapy on thesubject's brain activity;

(c) determining if the therapy causes adverse events;

(d) characterizing quantitatively the type, frequency, intensity andduration of the adverse effect;

(e) modifying the therapy to decrease the frequency, intensity,duration, or type of adverse effect; and

(f) logging to memory the optimized effects of the therapy on thesubject's brain activity.

In one embodiment, the present invention also provides a method forsemi-quantitative or qualitative assessment, optimization and logging ofthe adverse effects of a therapy for a medical condition. In oneembodiment, the method comprises:

(a) receiving into a signal processor input signals indicative of thesubject's brain activity and characterizing the spatio-temporal behaviorof the brain activity using the signals;

(b) characterizing the spatio-temporal effect of the therapy on thesubject's brain activity;

(c) determining if the therapy causes adverse events;

(d) characterizing semi-quantitatively or qualitatively the type,frequency, intensity and duration of the adverse effect;

(e) modifying the therapy to decrease the frequency, intensity,duration, or type of adverse effect; and

(f) logging to memory the optimized effects of the therapy on thesubject's brain activity.

FIGS. 38-39 shows a flowchart depiction of one method, in accordancewith the present invention. Turning to FIG. 38, a signal is acquired andprocessed 105, and analyzed 110. Based on the analysis 110, an event isdetected 115.

If no event is detected 115, flow returns to signal acquiring andprocessing 105. If an event is detected 115, a multi-featurecharacterization 120 is performed. Based on the multi-featurecharacterization 120, it is determined 125 if the event matches an entryin an event library.

If the event does not match, the event is saved 130 in a library ofunmatched events. A treatment library is then searched 135 for atreatment modality and parameters that may be efficacious in treatingthe event. A treatment is performed (not shown), and it is determined140 whether the treatment modality and parameters are efficacious. Ifthey are efficacious, this information is saved 145 in the treatmentlibrary. If not, flow returns to the search 135.

FIG. 39 shows a matched event analysis 200 taking place if the eventmatches an entry in an event library in determination 125. A treatmentlibrary is searched 235 for a treatment modality and parameters that maybe efficacious in treating the event. A treatment is delivered 237, andit is determined 240 whether the treatment modality and parameters areefficacious. If they are efficacious, flow returns to signal acquiringand processing 105.

If they are not efficacious, they are saved 245 in a nonefficacioustreatment library. A multi-feature characterization 250 is performed.Based on the multi-feature characterization 250, it is determined 255 ifthe event is of a new type, meaning one that does not match an entry inthe event library.

If the event is a new type according to determination 255, it is saved230 in a library of unmatched events, and flow returns to the search135.

If the event is not a new type according to determination 255, it isdetermined 260 if the treatment modality and parameters are accuratelymatched to the event type. If not, the treatment modality and parametersare changed, i.e., the error is corrected 265. However, if they areaccurately matched to the event type, they are retested 270. If theretested treatment modality and parameters are found 275 to beefficacious, this information is saved 280 in the treatment library. Ifnot, flow returns to the search 135.

Any method discussed herein may be performed by a computer readableprogram storage unit encoded with instructions that, when executed by acomputer, perform the method.

All of the methods and apparatuses disclosed and claimed herein may bemade and executed without undue experimentation in light of the presentdisclosure. While the methods and apparatus of this invention have beendescribed in terms of particular embodiments, it will be apparent tothose skilled in the art that variations may be applied to the methodsand apparatus and in the steps, or in the sequence of steps, of themethod described herein without departing from the concept, spirit, andscope of the invention, as defined by the appended claims. It should beespecially apparent that the principles of the invention may be appliedto selected cranial nerves other than, or in addition to, the vagusnerve to achieve particular results in treating patients havingepilepsy, depression, or other medical conditions.

Appendix: Cortex Morphometrics and electrical properties Human corticalthickness: mean: ˜2.5 mm (range: 1.45-4.5 mm). Approximately 80% ofcortical neurons are pyramidal. The intracellular space is in the orderof 100-200 A. Thalamic afferents to the cortex are grouped in bundles orcolumns with a diameter of 100-500-um. Cortical columns have a diameterof 200-500 nm. Cortical macrocolumns (diameter ˜0.5-3 mm; height ˜2.5mm) lies near the apparent theoretical limit of spatial resolutionavailable in scalp recordings. This macrocolumns apparently constitutesa distinct unit of neocortical dynamic function. Simultaneousinteractions can also be expected to take place at other spatial scales(for example between neurons, minicolumns, corticocortical columns ,cytoarchitectonic regions and so on. A cortical macrocolumn contains10{circumflex over ( )}5-10{circumflex over ( )}6 neurons and10{circumflex over ( )}10 synapses. The distance to which cells in themacrocolumn send collaterals (˜3 mm) provides one definition of theirspatial scale. Minicolumns (diameter ˜20-50 um) also has been proposedas a basic functional unit of neocortex; these can be defined by thecharacteristic lateral spread of axons of inhibitory neurons. Aminicolumn spanning the entire cortical thickness contains ˜110 neuronslined up along its axis (striate cortex contains ˜260 neurons)

Brodmann's identified two types of cortices in the human brain:

a) Homogenetic: Has 6 layers. It is also know as neocortex, isocortex,neopallium or supralimbic;

b) Heterogenetic: <6 layers. It is also known as allocortex. There are 2types of heterogenetic cortex: archipallium (hippocampus, dentate gymsand subiculum) and paleopallium (pyriform area). The transition betweenheterogenetic and homogenetic is known as mesocortex.

The particular embodiments disclosed above are illustrative only as theinvention may be modified and practiced in different but equivalentmanners apparent to those skilled in the art having the benefit of theteachings herein. Furthermore, no limitations are intended to thedetails of construction or design herein shown other than as describedin the claims below. It is, therefore, evident that the particularembodiments disclosed above may be altered or modified and all suchvariations are considered within the scope and spirit of the invention.Accordingly, the protection sought herein is as set forth in the claimsbelow.

What is claimed:
 1. A medical device configured to treat an epilepticevent comprising: one or more processors configured to determine a waverhythmicity of brain activity of a patient, and a treatment unitconfigured to apply a therapy to a target tissue of the patient at afirst time, wherein the target tissue and the first time are based uponthe wave rhythmicity.
 2. The medical device of claim 1, wherein thetherapy includes at least one of an electrical treatment, a thermaltreatment, a drug treatment, and a chemical treatment.
 3. The medicaldevice of claim 2, wherein the electrical treatment includes at leastone of: delivering direct currents; delivering alternating currents;delivering currents to multiple sites at one or more intensities;delivering currents to multiple sites at one or more frequencies;delivering currents to multiple sites at one or more pulse widths;delivering currents to multiple sites at one or more waveforms; anddelivering currents to multiple sites using one or more polarities. 4.The medical device of claim 1, wherein the one or more processors areconfigured to determine a second therapy based on patent specific data,where the second therapy is tailored to the patient.
 5. The medicaldevice of claim 4, wherein the treatment unit is further configured todeliver the second therapy to the patient.
 6. The medical device ofclaim 4, wherein at least one of: a time of therapy delivery; a therapyintensity; a therapy dosage; a type of therapy; a therapy deliverylocation; a geometric configuration; and a number of therapy sources arepart of the tailoring procedure.
 7. The medical device of claim 1,wherein the one or more processors are further configured to determine atherapy effect on a brain activity and modify the therapy based on thedetermined therapy effect on the brain activity.
 8. The medical deviceof claim 1, wherein the therapy has low efficacy based on a lowrhythmicity.
 9. The medical device of claim 8, wherein the one or moreprocessors are configured to initiate a second therapy based on the lowrhythmicity.
 10. The medical device of claim 1, wherein the one or moreprocessors are configured to generate a warning based on the waverhythmicity.